Overview

Dataset statistics

Number of variables43
Number of observations68358
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.4 MiB
Average record size in memory344.0 B

Variable types

CAT30
NUM11
BOOL2

Warnings

glimepiride-pioglitazone has constant value "68358" Constant
metformin-rosiglitazone has constant value "68358" Constant
diag_1 has a high cardinality: 691 distinct values High cardinality
diag_2 has a high cardinality: 715 distinct values High cardinality
diag_3 has a high cardinality: 755 distinct values High cardinality
number_emergency is highly skewed (γ1 = 21.11983727) Skewed
num_procedures has 29724 (43.5%) zeros Zeros
number_outpatient has 59309 (86.8%) zeros Zeros
number_emergency has 63267 (92.6%) zeros Zeros
number_inpatient has 60137 (88.0%) zeros Zeros

Reproduction

Analysis started2020-11-27 21:57:31.582889
Analysis finished2020-11-27 21:58:28.057531
Duration56.47 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

race
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
Caucasian
52638 
AfricanAmerican
12611 
Hispanic
 
1469
Other
 
1157
Asian
 
483
ValueCountFrequency (%) 
Caucasian5263877.0%
 
AfricanAmerican1261118.4%
 
Hispanic14692.1%
 
Other11571.7%
 
Asian4830.7%
 
2020-11-27T13:58:28.144595image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:28.253774image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:28.382502image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length9
Mean length9.989452588
Min length5

gender
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
Female
36440 
Male
31917 
Unknown/Invalid
 
1
ValueCountFrequency (%) 
Female3644053.3%
 
Male3191746.7%
 
Unknown/Invalid1< 0.1%
 
2020-11-27T13:58:28.573392image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-27T13:58:28.694723image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:28.827281image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length6
Mean length5.066312648
Min length4

age
Categorical

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
[70-80)
17588 
[60-70)
15373 
[50-60)
11960 
[80-90)
11202 
[40-50)
6498 
Other values (5)
5737 
ValueCountFrequency (%) 
[70-80)1758825.7%
 
[60-70)1537322.5%
 
[50-60)1196017.5%
 
[80-90)1120216.4%
 
[40-50)64989.5%
 
[30-40)25053.7%
 
[90-100)18362.7%
 
[20-30)9921.5%
 
[10-20)3400.5%
 
[0-10)640.1%
 
2020-11-27T13:58:29.023608image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:29.160982image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:29.338511image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length7
Mean length7.02592235
Min length6

admission_type_id
Real number (ℝ≥0)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.103586998
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size534.0 KiB
2020-11-27T13:58:29.521542image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile6
Maximum8
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.514801095
Coefficient of variation (CV)0.7201038495
Kurtosis1.590550016
Mean2.103586998
Median Absolute Deviation (MAD)0
Skewness1.51421207
Sum143797
Variance2.294622357
MonotocityNot monotonic
2020-11-27T13:58:29.752916image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
13500051.2%
 
31333819.5%
 
21221117.9%
 
644366.5%
 
530614.5%
 
82830.4%
 
720< 0.1%
 
49< 0.1%
 
ValueCountFrequency (%) 
13500051.2%
 
21221117.9%
 
31333819.5%
 
49< 0.1%
 
530614.5%
 
ValueCountFrequency (%) 
82830.4%
 
720< 0.1%
 
644366.5%
 
530614.5%
 
49< 0.1%
 

discharge_disposition_id
Real number (ℝ≥0)

Distinct26
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.636282513
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Memory size534.0 KiB
2020-11-27T13:58:29.956416image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile18
Maximum28
Range27
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.306901208
Coefficient of variation (CV)1.459430391
Kurtosis6.168915396
Mean3.636282513
Median Absolute Deviation (MAD)0
Skewness2.605951787
Sum248569
Variance28.16320043
MonotocityNot monotonic
2020-11-27T13:58:30.501115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%) 
14204561.5%
 
3848112.4%
 
6805311.8%
 
1824213.5%
 
214722.2%
 
2213932.0%
 
1110501.5%
 
58631.3%
 
257311.1%
 
44920.7%
 
Other values (16)13572.0%
 
ValueCountFrequency (%) 
14204561.5%
 
214722.2%
 
3848112.4%
 
44920.7%
 
58631.3%
 
ValueCountFrequency (%) 
28890.1%
 
273< 0.1%
 
257311.1%
 
2425< 0.1%
 
232530.4%
 

admission_source_id
Real number (ℝ≥0)

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.682012347
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Memory size534.0 KiB
2020-11-27T13:58:30.731407image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median7
Q37
95-th percentile17
Maximum25
Range24
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.173131386
Coefficient of variation (CV)0.7344460256
Kurtosis1.628406139
Mean5.682012347
Median Absolute Deviation (MAD)0
Skewness1.067740429
Sum388411
Variance17.41502556
MonotocityNot monotonic
2020-11-27T13:58:30.978509image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
73702354.2%
 
12094730.6%
 
1747867.0%
 
423733.5%
 
614862.2%
 
28591.3%
 
55360.8%
 
201540.2%
 
31310.2%
 
9360.1%
 
Other values (7)27< 0.1%
 
ValueCountFrequency (%) 
12094730.6%
 
28591.3%
 
31310.2%
 
423733.5%
 
55360.8%
 
ValueCountFrequency (%) 
252< 0.1%
 
224< 0.1%
 
201540.2%
 
1747867.0%
 
142< 0.1%
 

time_in_hospital
Real number (ℝ≥0)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.318177828
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Memory size534.0 KiB
2020-11-27T13:58:31.178842image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile11
Maximum14
Range13
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.958281921
Coefficient of variation (CV)0.6850764464
Kurtosis0.9325903281
Mean4.318177828
Median Absolute Deviation (MAD)2
Skewness1.158284422
Sum295182
Variance8.751431927
MonotocityNot monotonic
2020-11-27T13:58:31.501955image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
31209617.7%
 
21171917.1%
 
11008814.8%
 
4916313.4%
 
566119.7%
 
649867.3%
 
738655.7%
 
828284.1%
 
919292.8%
 
1015172.2%
 
Other values (4)35565.2%
 
ValueCountFrequency (%) 
11008814.8%
 
21171917.1%
 
31209617.7%
 
4916313.4%
 
566119.7%
 
ValueCountFrequency (%) 
146460.9%
 
137741.1%
 
129331.4%
 
1112031.8%
 
1015172.2%
 

num_lab_procedures
Real number (ℝ≥0)

Distinct116
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.13961789
Minimum1
Maximum132
Zeros0
Zeros (%)0.0%
Memory size534.0 KiB
2020-11-27T13:58:31.750965image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q131
median44
Q357
95-th percentile74
Maximum132
Range131
Interquartile range (IQR)26

Descriptive statistics

Standard deviation20.00539283
Coefficient of variation (CV)0.4637359764
Kurtosis-0.2920877578
Mean43.13961789
Median Absolute Deviation (MAD)13
Skewness-0.2138338676
Sum2948938
Variance400.2157422
MonotocityNot monotonic
2020-11-27T13:58:32.011090image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
121853.2%
 
4318372.7%
 
4415862.3%
 
4515622.3%
 
4614812.2%
 
3814682.1%
 
4714392.1%
 
4014272.1%
 
3913862.0%
 
3713802.0%
 
Other values (106)5260777.0%
 
ValueCountFrequency (%) 
121853.2%
 
27441.1%
 
34900.7%
 
42820.4%
 
52060.3%
 
ValueCountFrequency (%) 
1321< 0.1%
 
1211< 0.1%
 
1201< 0.1%
 
1181< 0.1%
 
1142< 0.1%
 

num_procedures
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.445156383
Minimum0
Maximum6
Zeros29724
Zeros (%)43.5%
Memory size534.0 KiB
2020-11-27T13:58:32.179739image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.763509343
Coefficient of variation (CV)1.220289627
Kurtosis0.5046128359
Mean1.445156383
Median Absolute Deviation (MAD)1
Skewness1.207174314
Sum98788
Variance3.109965201
MonotocityNot monotonic
2020-11-27T13:58:32.347582image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02972443.5%
 
11368720.0%
 
2885413.0%
 
3696510.2%
 
638215.6%
 
429634.3%
 
523443.4%
 
ValueCountFrequency (%) 
02972443.5%
 
11368720.0%
 
2885413.0%
 
3696510.2%
 
429634.3%
 
ValueCountFrequency (%) 
638215.6%
 
523443.4%
 
429634.3%
 
3696510.2%
 
2885413.0%
 

num_medications
Real number (ℝ≥0)

Distinct75
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.81316013
Minimum1
Maximum81
Zeros0
Zeros (%)0.0%
Memory size534.0 KiB
2020-11-27T13:58:32.537225image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q110
median14
Q320
95-th percentile31
Maximum81
Range80
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.290263264
Coefficient of variation (CV)0.5242635373
Kurtosis3.835930933
Mean15.81316013
Median Absolute Deviation (MAD)5
Skewness1.433092237
Sum1080956
Variance68.72846499
MonotocityNot monotonic
2020-11-27T13:58:32.755493image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1341766.1%
 
1241586.1%
 
1139145.7%
 
1538145.6%
 
1037635.5%
 
1437605.5%
 
1635735.2%
 
935065.1%
 
1732114.7%
 
831324.6%
 
Other values (65)3135145.9%
 
ValueCountFrequency (%) 
11940.3%
 
23330.5%
 
36270.9%
 
410281.5%
 
514682.1%
 
ValueCountFrequency (%) 
811< 0.1%
 
791< 0.1%
 
752< 0.1%
 
741< 0.1%
 
722< 0.1%
 

number_outpatient
Real number (ℝ≥0)

ZEROS

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2861406127
Minimum0
Maximum42
Zeros59309
Zeros (%)86.8%
Memory size534.0 KiB
2020-11-27T13:58:32.971396image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.084632662
Coefficient of variation (CV)3.790558258
Kurtosis179.5884764
Mean0.2861406127
Median Absolute Deviation (MAD)0
Skewness9.625457221
Sum19560
Variance1.176428012
MonotocityNot monotonic
2020-11-27T13:58:33.161103image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%) 
05930986.8%
 
147166.9%
 
219742.9%
 
310891.6%
 
45700.8%
 
52800.4%
 
61250.2%
 
7720.1%
 
8570.1%
 
9370.1%
 
Other values (23)1290.2%
 
ValueCountFrequency (%) 
05930986.8%
 
147166.9%
 
219742.9%
 
310891.6%
 
45700.8%
 
ValueCountFrequency (%) 
421< 0.1%
 
361< 0.1%
 
351< 0.1%
 
332< 0.1%
 
291< 0.1%
 

number_emergency
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1060007607
Minimum0
Maximum42
Zeros63267
Zeros (%)92.6%
Memory size534.0 KiB
2020-11-27T13:58:33.326635image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5161623841
Coefficient of variation (CV)4.869421509
Kurtosis1195.983411
Mean0.1060007607
Median Absolute Deviation (MAD)0
Skewness21.11983727
Sum7246
Variance0.2664236068
MonotocityNot monotonic
2020-11-27T13:58:33.513623image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%) 
06326792.6%
 
138795.7%
 
27861.1%
 
32410.4%
 
4950.1%
 
532< 0.1%
 
625< 0.1%
 
89< 0.1%
 
77< 0.1%
 
105< 0.1%
 
Other values (8)12< 0.1%
 
ValueCountFrequency (%) 
06326792.6%
 
138795.7%
 
27861.1%
 
32410.4%
 
4950.1%
 
ValueCountFrequency (%) 
421< 0.1%
 
371< 0.1%
 
251< 0.1%
 
201< 0.1%
 
161< 0.1%
 

number_inpatient
Real number (ℝ≥0)

ZEROS

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1814125633
Minimum0
Maximum12
Zeros60137
Zeros (%)88.0%
Memory size534.0 KiB
2020-11-27T13:58:33.663464image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6090359145
Coefficient of variation (CV)3.357187085
Kurtosis44.78560512
Mean0.1814125633
Median Absolute Deviation (MAD)0
Skewness5.449452586
Sum12401
Variance0.3709247451
MonotocityNot monotonic
2020-11-27T13:58:33.829865image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
06013788.0%
 
157968.5%
 
215122.2%
 
34800.7%
 
42300.3%
 
51010.1%
 
6550.1%
 
719< 0.1%
 
812< 0.1%
 
98< 0.1%
 
Other values (3)8< 0.1%
 
ValueCountFrequency (%) 
06013788.0%
 
157968.5%
 
215122.2%
 
34800.7%
 
42300.3%
 
ValueCountFrequency (%) 
122< 0.1%
 
111< 0.1%
 
105< 0.1%
 
98< 0.1%
 
812< 0.1%
 

diag_1
Categorical

HIGH CARDINALITY

Distinct691
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
414
 
5047
428
 
3875
786
 
2929
410
 
2810
486
 
2365
Other values (686)
51332 
ValueCountFrequency (%) 
41450477.4%
 
42838755.7%
 
78629294.3%
 
41028104.1%
 
48623653.5%
 
42719932.9%
 
71518312.7%
 
43415432.3%
 
68214042.1%
 
78013832.0%
 
Other values (681)4317863.2%
 
2020-11-27T13:58:34.061056image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique101 ?
Unique (%)0.1%
2020-11-27T13:58:34.340170image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length3
Mean length3.150823605
Min length1

diag_2
Categorical

HIGH CARDINALITY

Distinct715
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
250
 
4404
276
 
4397
428
 
4222
427
 
3443
401
 
2972
Other values (710)
48920 
ValueCountFrequency (%) 
25044046.4%
 
27643976.4%
 
42842226.2%
 
42734435.0%
 
40129724.3%
 
59922013.2%
 
49621693.2%
 
41119792.9%
 
41419112.8%
 
40315882.3%
 
Other values (705)3907257.2%
 
2020-11-27T13:58:34.577123image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique121 ?
Unique (%)0.2%
2020-11-27T13:58:34.776770image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length3
Mean length3.176014512
Min length1

diag_3
Categorical

HIGH CARDINALITY

Distinct755
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
250
8739 
401
6406 
276
 
3383
428
 
2785
427
 
2637
Other values (750)
44408 
ValueCountFrequency (%) 
250873912.8%
 
40164069.4%
 
27633834.9%
 
42827854.1%
 
42726373.9%
 
41425853.8%
 
49616142.4%
 
27215782.3%
 
40312721.9%
 
59912541.8%
 
Other values (745)3610552.8%
 
2020-11-27T13:58:35.002113image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique137 ?
Unique (%)0.2%
2020-11-27T13:58:35.202013image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length3
Mean length3.133459142
Min length1

number_diagnoses
Real number (ℝ≥0)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.349044735
Minimum3
Maximum16
Zeros0
Zeros (%)0.0%
Memory size534.0 KiB
2020-11-27T13:58:35.351799image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q16
median8
Q39
95-th percentile9
Maximum16
Range13
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.884518736
Coefficient of variation (CV)0.2564304347
Kurtosis-0.609153816
Mean7.349044735
Median Absolute Deviation (MAD)1
Skewness-0.6769684049
Sum502366
Variance3.551410867
MonotocityNot monotonic
2020-11-27T13:58:35.524514image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
93107945.5%
 
5827412.1%
 
6753611.0%
 
7742810.9%
 
8738210.8%
 
443076.3%
 
322843.3%
 
1627< 0.1%
 
1310< 0.1%
 
108< 0.1%
 
Other values (4)23< 0.1%
 
ValueCountFrequency (%) 
322843.3%
 
443076.3%
 
5827412.1%
 
6753611.0%
 
7742810.9%
 
ValueCountFrequency (%) 
1627< 0.1%
 
155< 0.1%
 
145< 0.1%
 
1310< 0.1%
 
127< 0.1%
 

max_glu_serum
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
None
65026 
Norm
 
1672
>200
 
936
>300
 
724
ValueCountFrequency (%) 
None6502695.1%
 
Norm16722.4%
 
>2009361.4%
 
>3007241.1%
 
2020-11-27T13:58:35.819321image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:36.341319image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:36.873746image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

A1Cresult
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
None
56126 
>8
5766 
Norm
 
3668
>7
 
2798
ValueCountFrequency (%) 
None5612682.1%
 
>857668.4%
 
Norm36685.4%
 
>727984.1%
 
2020-11-27T13:58:37.135728image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:37.244644image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:37.410549image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length3.749436789
Min length2

metformin
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
54032 
Steady
13120 
Up
 
793
Down
 
413
ValueCountFrequency (%) 
No5403279.0%
 
Steady1312019.2%
 
Up7931.2%
 
Down4130.6%
 
2020-11-27T13:58:37.600352image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:37.710229image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:38.190609image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.779806314
Min length2

repaglinide
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
67448 
Steady
 
811
Up
 
70
Down
 
29
ValueCountFrequency (%) 
No6744898.7%
 
Steady8111.2%
 
Up700.1%
 
Down29< 0.1%
 
2020-11-27T13:58:38.387344image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:38.498723image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:38.662822image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.048304514
Min length2

nateglinide
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
67870 
Steady
 
464
Up
 
16
Down
 
8
ValueCountFrequency (%) 
No6787099.3%
 
Steady4640.7%
 
Up16< 0.1%
 
Down8< 0.1%
 
2020-11-27T13:58:38.873224image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:39.003018image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:39.138272image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.027385237
Min length2

chlorpropamide
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68289 
Steady
 
64
Up
 
4
Down
 
1
ValueCountFrequency (%) 
No6828999.9%
 
Steady640.1%
 
Up4< 0.1%
 
Down1< 0.1%
 
2020-11-27T13:58:39.332368image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-27T13:58:39.454710image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:39.777405image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.003774247
Min length2

glimepiride
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
64782 
Steady
 
3219
Up
 
226
Down
 
131
ValueCountFrequency (%) 
No6478294.8%
 
Steady32194.7%
 
Up2260.3%
 
Down1310.2%
 
2020-11-27T13:58:40.043205image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:40.178889image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:41.063817image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.192194037
Min length2

acetohexamide
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68357 
Steady
 
1
ValueCountFrequency (%) 
No68357> 99.9%
 
Steady1< 0.1%
 
2020-11-27T13:58:41.368541image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-27T13:58:41.543862image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:41.672992image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.000058515
Min length2

glipizide
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
59593 
Steady
7836 
Up
 
566
Down
 
363
ValueCountFrequency (%) 
No5959387.2%
 
Steady783611.5%
 
Up5660.8%
 
Down3630.5%
 
2020-11-27T13:58:41.975472image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:42.275380image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:42.554511image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.469147722
Min length2

glyburide
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
60843 
Steady
6516 
Up
 
601
Down
 
398
ValueCountFrequency (%) 
No6084389.0%
 
Steady65169.5%
 
Up6010.9%
 
Down3980.6%
 
2020-11-27T13:58:42.816907image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:42.956209image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:43.087949image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.392931332
Min length2

tolbutamide
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68340 
Steady
 
18
ValueCountFrequency (%) 
No68340> 99.9%
 
Steady18< 0.1%
 
2020-11-27T13:58:43.294278image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:43.410426image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:43.555916image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.001053278
Min length2

pioglitazone
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
63253 
Steady
 
4853
Up
 
173
Down
 
79
ValueCountFrequency (%) 
No6325392.5%
 
Steady48537.1%
 
Up1730.3%
 
Down790.1%
 
2020-11-27T13:58:43.748446image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:43.860260image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:44.030373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.286286901
Min length2

rosiglitazone
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
63830 
Steady
 
4324
Up
 
132
Down
 
72
ValueCountFrequency (%) 
No6383093.4%
 
Steady43246.3%
 
Up1320.2%
 
Down720.1%
 
2020-11-27T13:58:44.218239image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:44.323012image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:44.462156image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.255127417
Min length2

acarbose
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68164 
Steady
 
184
Up
 
10
ValueCountFrequency (%) 
No6816499.7%
 
Steady1840.3%
 
Up10< 0.1%
 
2020-11-27T13:58:44.674255image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:44.794485image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:44.938114image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.010766845
Min length2

miglitol
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68338 
Steady
 
18
Up
 
1
Down
 
1
ValueCountFrequency (%) 
No68338> 99.9%
 
Steady18< 0.1%
 
Up1< 0.1%
 
Down1< 0.1%
 
2020-11-27T13:58:45.145033image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-11-27T13:58:45.263467image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:45.425457image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.001082536
Min length2

troglitazone
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68355 
Steady
 
3
ValueCountFrequency (%) 
No68355> 99.9%
 
Steady3< 0.1%
 
2020-11-27T13:58:45.622113image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:45.723119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:45.861763image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.000175546
Min length2

tolazamide
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68330 
Steady
 
28
ValueCountFrequency (%) 
No68330> 99.9%
 
Steady28< 0.1%
 
2020-11-27T13:58:46.070869image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:46.180828image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:46.306379image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.001638433
Min length2

insulin
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
33636 
Steady
20888 
Down
7211 
Up
6623 
ValueCountFrequency (%) 
No3363649.2%
 
Steady2088830.6%
 
Down721110.5%
 
Up66239.7%
 
2020-11-27T13:58:46.515225image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:46.622286image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:46.766299image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length3.433248486
Min length2
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
67885 
Steady
 
464
Up
 
6
Down
 
3
ValueCountFrequency (%) 
No6788599.3%
 
Steady4640.7%
 
Up6< 0.1%
 
Down3< 0.1%
 
2020-11-27T13:58:46.987214image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:47.175000image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:47.351586image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.027238948
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68351 
Steady
 
7
ValueCountFrequency (%) 
No68351> 99.9%
 
Steady7< 0.1%
 
2020-11-27T13:58:47.553337image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:47.664740image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:47.797333image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.000409608
Min length2

glimepiride-pioglitazone
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68358 
ValueCountFrequency (%) 
No68358100.0%
 
2020-11-27T13:58:47.995558image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:48.094657image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:48.207849image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

metformin-rosiglitazone
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68358 
ValueCountFrequency (%) 
No68358100.0%
 
2020-11-27T13:58:48.363409image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:48.459475image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:48.591983image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
68357 
Steady
 
1
ValueCountFrequency (%) 
No68357> 99.9%
 
Steady1< 0.1%
 
2020-11-27T13:58:48.757187image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-27T13:58:48.856967image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:48.985788image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.000058515
Min length2

change
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
No
37782 
Ch
30576 
ValueCountFrequency (%) 
No3778255.3%
 
Ch3057644.7%
 
2020-11-27T13:58:49.180018image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-27T13:58:49.282162image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:49.405018image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
Yes
51789 
No
16569 
ValueCountFrequency (%) 
Yes5178975.8%
 
No1656924.2%
 
2020-11-27T13:58:49.511577image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

readmitted
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size534.0 KiB
NO
40729 
YES
27629 
ValueCountFrequency (%) 
NO4072959.6%
 
YES2762940.4%
 
2020-11-27T13:58:49.577924image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Interactions

2020-11-27T13:58:06.051553image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:06.311208image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:06.561201image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:06.762719image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:06.939911image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:07.130795image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:07.318463image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:07.564690image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:07.788303image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:07.981535image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:08.172881image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:08.359594image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:08.497688image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:08.622792image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:08.838025image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:09.069667image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:09.265344image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:09.591130image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:09.726248image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:09.926752image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:10.228813image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:10.447423image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:10.580181image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:10.712329image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:10.826799image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:10.974592image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:11.107549image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:11.246089image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:11.364699image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:11.502575image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:11.615426image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:11.726234image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:11.844136image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:11.982075image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:12.109120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:12.233803image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:12.355398image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:12.479295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:12.611119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:12.732190image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:12.864760image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:12.987785image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:13.105564image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:13.236999image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:13.361000image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:13.485446image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:13.619644image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:13.741392image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:13.872104image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:13.999157image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:14.116679image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:14.357936image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:14.486381image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:14.643561image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:14.763032image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:14.881139image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:15.000800image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:15.117600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:15.245191image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:15.376820image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:15.506160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:15.645862image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:15.802278image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:15.921007image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:16.040142image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:16.161947image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:16.278618image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:16.404064image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:16.533129image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:16.676066image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:16.808120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:16.949128image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:17.083409image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:17.215195image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:17.335112image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:17.455375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:17.600162image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:17.738025image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:17.852651image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:17.962936image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:18.073294image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:18.208765image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:18.355608image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:18.530612image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:18.681722image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:18.792276image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:18.898235image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:19.014616image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:19.127670image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:19.249382image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:19.381800image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:19.532313image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:19.661587image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:19.958786image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:20.107355image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:20.240789image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:20.359073image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:20.483194image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:20.615345image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:20.749008image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:20.882006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:21.042463image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:21.173037image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:21.302741image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:21.435660image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:21.576987image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:21.780041image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:21.932608image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:22.095702image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:22.269024image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:22.482596image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:22.684788image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:22.826690image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:22.989341image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:23.187057image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:23.365579image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:23.529543image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:23.731836image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:23.873876image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:24.016742image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:24.204064image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-11-27T13:58:49.672207image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-27T13:58:49.876096image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-27T13:58:50.146620image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-27T13:58:50.418913image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-27T13:58:50.813787image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-27T13:58:25.068631image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-11-27T13:58:27.105533image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

racegenderageadmission_type_iddischarge_disposition_idadmission_source_idtime_in_hospitalnum_lab_proceduresnum_proceduresnum_medicationsnumber_outpatientnumber_emergencynumber_inpatientdiag_1diag_2diag_3number_diagnosesmax_glu_serumA1Cresultmetforminrepaglinidenateglinidechlorpropamideglimepirideacetohexamideglipizideglyburidetolbutamidepioglitazonerosiglitazoneacarbosemiglitoltroglitazonetolazamideinsulinglyburide-metforminglipizide-metforminglimepiride-pioglitazonemetformin-rosiglitazonemetformin-pioglitazonechangediabetesMedreadmitted
0CaucasianFemale[10-20)117359018000276250.012559NoneNoneNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoUpNoNoNoNoNoChYesYES
1AfricanAmericanFemale[20-30)117211513201648250V276NoneNoneNoNoNoNoNoNoSteadyNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoYesNO
2CaucasianMale[30-40)1172441160008250.434037NoneNoneNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoUpNoNoNoNoNoChYesNO
3CaucasianMale[40-50)117151080001971572505NoneNoneNoNoNoNoNoNoSteadyNoNoNoNoNoNoNoNoSteadyNoNoNoNoNoChYesNO
4CaucasianMale[50-60)2123316160004144112509NoneNoneNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoSteadyNoNoNoNoNoNoYesYES
5CaucasianMale[60-70)312470121000414411V457NoneNoneSteadyNoNoNoSteadyNoNoNoNoNoNoNoNoNoNoSteadyNoNoNoNoNoChYesNO
6CaucasianMale[70-80)1175730120004284922508NoneNoneNoNoNoNoNoNoNoSteadyNoNoNoNoNoNoNoNoNoNoNoNoNoNoYesYES
7CaucasianFemale[80-90)2141368228000398427388NoneNoneNoNoNoNoNoNoSteadyNoNoNoNoNoNoNoNoSteadyNoNoNoNoNoChYesNO
8CaucasianFemale[90-100)33412333180004341984868NoneNoneNoNoNoNoNoNoNoNoNoNoSteadyNoNoNoNoSteadyNoNoNoNoNoChYesNO
9AfricanAmericanFemale[40-50)117947217000250.74039969NoneNoneNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoSteadyNoNoNoNoNoNoYesYES

Last rows

racegenderageadmission_type_iddischarge_disposition_idadmission_source_idtime_in_hospitalnum_lab_proceduresnum_proceduresnum_medicationsnumber_outpatientnumber_emergencynumber_inpatientdiag_1diag_2diag_3number_diagnosesmax_glu_serumA1Cresultmetforminrepaglinidenateglinidechlorpropamideglimepirideacetohexamideglipizideglyburidetolbutamidepioglitazonerosiglitazoneacarbosemiglitoltroglitazonetolazamideinsulinglyburide-metforminglipizide-metforminglimepiride-pioglitazonemetformin-rosiglitazonemetformin-pioglitazonechangediabetesMedreadmitted
68348CaucasianFemale[40-50)14714690160002953052505None>7UpNoNoNoNoNoNoSteadyNoNoNoNoNoNoNoDownNoNoNoNoNoChYesYES
68349CaucasianFemale[70-80)3613271290107154012509NoneNormSteadyNoNoNoNoNoSteadyNoNoNoNoNoNoNoNoSteadyNoNoNoNoNoChYesNO
68350CaucasianMale[70-80)361137766500042442948616NoneNormNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoUpNoNoNoNoNoChYesNO
68351OtherFemale[40-50)311313150003487847828NoneNoneSteadyNoNoNoNoNoNoSteadyNoNoNoNoNoNoNoSteadyNoNoNoNoNoChYesNO
68352OtherMale[40-50)1171351213000250.87307319NoneNoneSteadyNoNoNoNoNoNoNoNoNoNoNoNoNoNoDownNoNoNoNoNoChYesNO
68353CaucasianFemale[70-80)117950233000574574250.029None>7NoNoNoNoNoNoNoUpNoNoNoNoNoNoNoSteadyNoNoNoNoNoChYesYES
68354OtherFemale[40-50)11714736260105925995189None>8NoNoNoNoNoNoSteadyNoNoNoNoNoNoNoNoUpNoNoNoNoNoChYesYES
68355OtherFemale[60-70)1172466171119965854039NoneNoneNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoSteadyNoNoNoNoNoNoYesYES
68356CaucasianFemale[80-90)11757612201029283049NoneNoneNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoUpNoNoNoNoNoChYesNO
68357CaucasianMale[70-80)117613330005305307879NoneNoneNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNO